Improving Insights on Air Pollutant Mixtures and Their Origins by Enhancing Local Monitoring in an Area of Intensive Resource Development

An “event-based” approach to characterize complex air pollutant mixtures was applied in the Oil Sands region of northern Alberta, Canada. This approach was developed to better-inform source characterization and attribution of the air pollution in the Indigenous community of Fort McKay, within the context of the lived experience of residents. Principal component analysis was used to identify the characteristics of primary pollutant mixtures, which were related to hydrocarbon emissions, fossil fuel combustion, dust, and oxidized and reduced sulfur compounds. Concentration distributions of indicator compounds were used to isolate sustained air pollution “events”. Diesel-powered vehicles operating in the mines were found to be an important source during NOx events. Industry-specific volatile organic compound (VOC) profiles were used in a chemical mass balance model for source apportionment, which revealed that nearby oil sands operations contribute to 86% of the total mass of nine VOC species (2-methylpentane, hexane, heptane, octane, benzene, toluene, m,p-xylene, o-xylene, and ethylbenzene) during VOC events. Analyses of the frequency distribution of air pollution events indicate that Fort McKay is regularly impacted by multiple mixtures simultaneously, underscoring the limitations of an exceedance-based approach relying on a small number of air quality standards as the only tool to assess risk.

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Field Value
Short Name of Publication Improving Insights on Air Pollutant Mixtures and Their Origins by Enhancing Local Monitoring in an Area of Intensive Resource Development
Deliverable Type Journal Article
Program Catagory Air
Program Type OSM
Author
Periodical Title Environmental Science & Technology
Year of Publication 2020
Publishing Organization ECCC
Month of Publication
Periodical Volumes 54 (23)
Page Range 14936-14945
Digital Object Identifier (DOI) 10.1021/acs.est.0c06055
Online ISBN/ISSN
Print ISBN/ISSN
Recomended Citation Sumi N. Wren, Cris M. Mihele, Gang Lu, Zhimei Jiang, Deyong Wen, Katherine Hayden, Richard L. Mittermeier, Ralf M. Staebler, Stewart G. Cober, and Jeffrey R. Brook Environmental Science & Technology 2020 54 (23), 14936-14945 DOI: 10.1021/acs.est.0c06055
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